The Human UGT1A3 Enzyme Conjugates Norursodeoxycholic Acid into a C23-ester Glucuronide in the Liver
Bibliographic record
Abstract
Norursodeoxycholic acid (norUDCA) exhibits efficient anti-cholestatic properties in an animal model of sclerosing cholangitis. norUDCA is eliminated as a C(23)-ester glucuronide (norUDCA-23G) in humans. The present study aimed at identifying the human UDP-glucuronosyltransferase (UGT) enzyme(s) involved in hepatic norUDCA glucuronidation and at evaluating the consequences of single nucleotide polymorphisms in the coding region of UGT genes on norUDCA-23G formation. The effects of norUDCA on the formation of the cholestatic lithocholic acid-glucuronide derivative and of rifampicin on hepatic norUDCA glucuronidation were also explored. In vitro glucuronidation assays were performed with microsomes from human tissues (liver and intestine) and HEK293 cells expressing human UGT enzymes and variant allozymes. UGT1A3 was identified as the major hepatic UGT enzyme catalyzing the formation of norUDCA-23G. Correlation studies using samples from a human liver bank (n = 16) indicated that the level of UGT1A3 protein is a strong determinant of in vitro norUDCA glucuronidation. Analyses of the norUDCA-conjugating activity by 11 UGT1A3 variant allozymes identified three phenotypes with high, low, and intermediate capacity. norUDCA is also identified as a competitive inhibitor for the hepatic formation of the pro-cholestatic lithocholic acid-glucuronide derivative, whereas norUDCA glucuronidation is weakly stimulated by rifampicin. This study identifies human UGT1A3 as the major enzyme for the hepatic norUDCA glucuronidation and supports that some coding polymorphisms affecting the conjugating activity of UGT1A3 in vitro may alter the pharmacokinetic properties of norUDCA in cholestasis treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".